This disclosure relates generally to image registration systems, and more particularly to image registration systems utilized for visual object tracking.
Many video analytics systems utilize automatic image registration techniques to geometrically align two images taken at different times, from different viewpoints, or both. For instance, imaging seekers used for, e.g., target tracking in weapon guidance systems, typically use automatic image registration to separate changes in object location from rotations of the seeker's field of view as captured by a sequence of images. Such image registration typically involves image feature selection and correspondence between stationary objects (often referred to as landmarks) in the field of view, as well as reshaping and resampling of one image to align it to the other image via a transformation function.
Image registration via stationary landmarks is hindered when no common landmarks are available within the field of view (e.g., over large bodies of water), or when repetitive landmarks make feature correspondence ambiguous, such as when the background field of view consists of repeating or tiled patterns. Accordingly, image registration for visual object tracking via image feature selection alone can decrease performance of the visual object tracking system to provide target and guidance information when the field of view passes over areas devoid of landmarks or having ambiguous landmark features.